Assessing background particulate contamination in an historic building – surface lead loading and contamination

ABSTRACT

Investigation of suspect surface contamination in a building may require comparative sampling across different zones to provide meaningful information with regard to contaminant sources, pathways and/or extent of dispersal. However, evaluation of the data using traditional null hypothesis significance testing (NHST) based upon the mean may result in misleading inference when encountering erratic distributions typical of environmental contaminant data. Sampling data (n = 90) for lead content in surface dust collected throughout a historic building with suspect contamination from uncontrolled disturbance to lead coatings were evaluated using traditional NHST and randomization/permutation inference; the latter metric was the maximum difference in frequency of detection (Δfd _max), to directly calculate the probability of the observed differences. In the examples for lead in surface dust presented herein, areas with “lower” mean concentration and/or no significant difference via NHST actually represented “greater contamination,” as Δfd _max indicated a greater probability of encountering lead at higher concentrations. Resulting conclusions with regard to sources and pathways contradicted those generated from traditional NHST, and underscore the need to recognize differences in applicability of different inference approaches, depending upon the distribution of the data and the particular problem. This is particularly relevant for forensic purposes.     

3D MRI measurements of the effects of wind direction on flow characteristics and contaminant dispersion in a model urban canopy

Environmental Fluid Mechanics - Three dimensional velocity fields and contaminant dispersion within an evenly spaced orthogonal array of cubic buildings (height = H) with a central tall...     

Evaluation of compositional characteristics of organic waste shares in municipal solid waste in fast-growing metropolitan cities of India

Journal of Material Cycles and Waste Management - India currently has the second largest urban population worldwide, while facing an increasing burden on its urban solid waste infrastructure. To...     

Effects of seascape connectivity on reserve performance along exposed coastlines

Seascape connectivity (landscape connectivity in the sea) can modify reserve performance in low-energy marine ecosystems (e.g., coral reefs, mangroves, and seagrass), but it is not clear whether similar spatial linkages also shape reserve effectiveness on high-energy, exposed coastlines. We used the surf zones of ocean beaches in eastern Australia as a model system to test how seascape connectivity and reserve attributes combine to shape conservation outcomes. Spatial patterns in fish assemblages were measured using baited remote underwater video stations in 12 marine reserves and 15 fished beaches across 2000 km of exposed coastline. Reserve performance was shaped by both the characteristics of reserves and the spatial properties of the coastal seascapes in which reserves were embedded. Number of fish species and abundance of harvested fishes were highest in surf-zone reserves that encompassed >1.5 km of the surf zone; were located < 100 m to rocky headlands; and included pocket beaches in a heterogeneous seascape. Conservation outcomes for exposed coastlines may, therefore, be enhanced by prioritizing sufficiently large areas of seascapes that are strongly linked to abutting complementary habitats. Our findings have broader implications for coastal conservation planning. Empirical data to describe how the ecological features of high-energy shorelines influence conservation outcomes are lacking, and we suggest that seascape connectivity may have similar ecological effects on reserve performance on both sheltered and exposed coastlines.     

Rabbit Population Landscape-Scale Simulation to Investigate the Relevance of Using Rabbits in Regulatory Environmental Risk Assessment

This paper describes the development and testing of the ALMaSS rabbit model and its baseline, and subsequently its application to the question of lagomorph population vulnerability in environmental risk assessment (ERA). Development and testing following a pattern-oriented modelling protocol resulted in a model able to replicate local and landscape-level rabbit population patterns. We then tested how robust rabbit populations are to an (imaginary) extreme toxic stressor at a landscape level in a variety of landscapes, and to what extremes key uncertain model parameters must be pushed to cause extinctions. This was contrasted with the same (imaginary) toxic stressor applied to the already existing ALMaSS hare model. For EU risk assessment of plant protection products, these results clearly indicate that if the protection goal is population-level impacts, either in abundance and/or distribution, then the hare is a much more vulnerable species than the rabbit under all the conditions tested. Rabbits would only be more vulnerable than hares if the entire population were to be exposed simultaneously, when lower body mass would then be a critical factor. This did not occur even though the toxicant and exposure scenarios tested here were extreme and, in fragmented landscapes at scales used here, will not occur in reality from the use of plant protection products on crop fields. As well as specifically answering the question on rabbit versus hare vulnerability, this study generally illustrates the potential application of models for setting focal species for risk assessments.     

Decision framework for evaluating the macroeconomic risks and policy impacts of cyber attacks

Increased reliance on the Internet for critical infrastructure and the global nature of supply chains provides an opportunity for adversaries to leverage dependencies and gain access to vital infrastructure. Traditional approaches to assessing risk in the cyber domain, including estimation of impacts, fall short due to uncertainty in how interconnected systems react to cyber attack. This paper describes a method to represent the pathways of disruption propagation, evaluate the macroeconomic impact of cyber threats and aid in selecting among various cybersecurity policies. Based on state of the art agent-based modeling, multicriteria decision analysis, and macroeconomic modeling tools, this framework provides dynamic macroeconomic, demographic and fiscal insights regarding shocks caused by cyber attacks to the regional economy over time. The interlinkage of these models will provide a robust and adaptive system that allows policy makers to evaluate complex issues such as cybersecurity threats and their impacts on the geopolitical, social, environmental, and macroeconomic landscape.     

Universities and Climate Change Mitigation: Advancing Grassroots Climate Policy in the US

Abstract

While US climate change mitigation policy has stalled at the national level, local and regional actors are increasingly taking progressive steps to reduce their greenhouse gas emissions. Universities are poised to play a key role in this grassroots effort by targeting their own emissions and by working with other local actors to develop climate change mitigation programmes. Researchers at the Pennsylvania State University have collaborated with university administrators and personnel to inventory campus emissions and develop mitigation strategies. In addition, they have facilitated a stakeholder-driven climate change mitigation project in one Pennsylvania county and started an ongoing service-learning project aimed at reducing emissions in another county. These campus and community outreach initiatives demonstrate that university-based mitigation action may simultaneously achieve tangible local benefits and develop solutions to broader challenges facing local climate change mitigation efforts. Outcomes include improved tools and protocols for measuring and reducing local emissions, lessons learned about service-learning approaches to climate change mitigation, and methods for creating climate change governance networks involving universities, local governments and community stakeholders.     

Pulverized coal stream ignition delay under conventional and oxy-fuel combustion conditions

The coal stream ignition process is critical to the performance of modern pulverized coal burners, particularly when operating under novel conditions such as experienced in oxy-fuel combustion. However, experimental studies of coal stream ignition are lacking, and recent modeling efforts have had to rely on comparisons with a single set of experiments in vitiated air. To begin to address this shortfall, we have conducted experiments on the ignition properties of two U.S. and two Chinese coals in a laminar entrained flow reactor. Most of the measurements focused on varying the coal feed rate for furnace temperatures of 1230–1320 K and for 12–20 vol.% O₂ in nitrogen. The influence of coal feed rate on ignition with a carbon dioxide diluent was also measured for 20 vol.% O₂ at 1280 K. A second set of measurements was performed for ignition of a fixed coal feed rate in N₂ and CO₂ environments at identical furnace temperatures of 1200 K, 1340 K, and 1670 K. A scientific CCD camera equipped with a 431 nm imaging filter was used to interrogate the ignition process. Under most conditions, the ignition delay decreased with increasing coal feed rate until a minimum was reached at a feed rate corresponding to a particle number density of approximately 4 × 10⁹ m^?3 in the coal feed pipe. This ignition minimum corresponds to a cold flow group number, G, of ～0.3. At higher coal feed rates the ignition delay increased. The ignition delay time was shown to be very sensitive to (a) the temperature of the hot coflow into which the coal stream is introduced, and (b) the coal particle size. The three high volatile bituminous coals showed nearly identical ignition delay as a function of coal feed rate, whereas the subbituminous coal showed slightly greater apparent ignition delay. Bath gas CO₂ content was found to have a minor impact on ignition delay.     

Reuse of spent bleaching earth by polymerisation of residual organics

Spent bleaching earth (SBE) is a waste generated by the edible oil industry that currently has limited options for beneficial reuse. In excess of ～2 million tonnes per year of SBE is generated world-wide with major quantities available in the middle-east where significant volumes of edible oils are produced. Low pressure compaction followed by heat treatment at 150 °C causes polymerisation of the residual organic components in SBE and this produces monolithic samples with high unconfined compressive strengths (54 MPa). SBE can therefore be used to manufacture novel clay blocks for use in construction that are bonded by polymerised vegetable oil. This represents a new, innovative and resource efficient application for SBE. In this research, commercial SBE has been characterised and the effects of key processing variables (temperature and compaction pressure) on the compressive strength, porosity and density of the SBE clay blocks are reported and the mechanisms responsible for strength development are discussed.     

Capitalizing property rights insecurity in natural resource assets

Property rights are commonly touted as a solution to common pool resource problems. In practice, however, the security of property rights over natural resources varies substantially; this may affect returns to ownership and asset values. We use an analytical model to examine the effects of insecure property rights to natural resources on the market value of assets. We then use a unique dataset of fisheries from three countries to examine empirically how differences in property rights affect market outcomes. We find significant asset market capitalization of insecurity arising from (1) ownership disputes, (2) illegal extraction from resource stocks, and (3) the possibility of government revocation of rights.